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Taxonomic reasoning in LOGIDATA+

  • Part III: Complex Objects
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LOGIDATA+: Deductive Databases with Complex Objects

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 701))

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Abstract

Taxonomic reasoning is a typical inference task performed by many AI knowledge representation systems. We illustrate the effectiveness of taxonomic reasoning techniques as an active support to knowledge acquisition and schemas design in the advanced database environment LOGIDATA+, supporting complex objects and a rule-based language. The developed idea is that, by extending complex object data models with defined classes, it is possible to infer ISA relationships (i.e. compute subsumption) between classes on the basis of their descriptions. From a theoretical point of view, this approach makes it possible to give a formal definition of consistency to a schema, while, from a pragmatic point of view, it is possible to automatically classify a new class in the correct position of a given taxonomy.

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Author information

Authors and Affiliations

  1. CIOC-CNR, Universita di Bologna, Italia

    Domenico Beneventano, Sonia Bergamaschi & Claudio Sartori

  2. Dipartimento di Sistemi e Informatica, Universita di Firenze, Italia

    Alessandro Artale, Francesca Cesarini & Giovanni Soda

Authors
  1. Domenico Beneventano
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  2. Sonia Bergamaschi
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  3. Claudio Sartori
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  4. Alessandro Artale
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  5. Francesca Cesarini
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  6. Giovanni Soda
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Editor information

Paolo Atzeni

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© 1993 Springer-Verlag Berlin Heidelberg

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Beneventano, D., Bergamaschi, S., Sartori, C., Artale, A., Cesarini, F., Soda, G. (1993). Taxonomic reasoning in LOGIDATA+ . In: Atzeni, P. (eds) LOGIDATA+: Deductive Databases with Complex Objects. Lecture Notes in Computer Science, vol 701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0021891

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  • DOI: https://doi.org/10.1007/BFb0021891

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-56974-9

  • Online ISBN: 978-3-540-47844-7

  • eBook Packages: Springer Book Archive

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